Functional near-infrared spectroscopy as a monitor for depth of anesthesia

ABSTRACT

Disclosed are methods and devices for measuring a state of anesthesia in a noninvasive manner. Optical techniques may be used to measure changes in a functional near-infrared (fNIR) signal, where the fNIR signal is received in response to directing wavelengths of light in a near-infrared range on a patient. The optical density change may be used to obtain a change in deoxyhemoglobin (deoxy-Hb) concentration and/or a change in an oxyhemoglobin concentration (oxy-Hb). The changes in the deoxy-Hb and/or the oxy-Hb may then be compared to determine a state of anesthesia. 
     The effect of artifacts (e.g., strong surgery room lighting, patient-table tilting, patient intubation/extubation) on the fNIR signal may be removed using a noise removal algorithm. In selecting the noise removal algorithm, a switching technique may be used to select the component analysis algorithm, such as a principal component analysis (PCA), an independent component analysis (ICA), or the like.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority under 35 U.S.C. §119 (e) to U.S.provisional application Ser. No. 61/101,671, filed on Sep. 30, 2009,entitled “Functional Near-Infrared Spectroscopy as a Monitor for Depthof Anesthesia,” which is herein incorporated by reference in itsentirety.

BACKGROUND

It is known that fear, dread, panic, and excruciating pain may accompanyunintended awareness during anesthesia. During this anesthesia state,patients may recall events or conversations that occurred in theoperation room. These incidents are not benign. For example, someincidents have resulted in posttraumatic stress disorder. Prevention ofunintended awareness during anesthesia may be accomplished by having analert anesthesia clinician monitor an anesthetized patient's vitalsigns. However, vital signs may not provide a sufficient warning. Forexample, vital signs may not provide a sufficient warning in elderlyanesthetized patients with comorbid conditions such as hypertension ortachycardia.

There has been interest in developing state of anesthesia devices thatcan continuously and reliably monitor the anesthesia state during asurgical procedure. Such devices have largely been based on themeasurement of electrophysiological signals such as electrocardiographic(ECG) signals, electroencephalographic (EEG) signals, auditory andsomatosensory evoked potentials, and craniofacial electromographic (EMG)signals. Unfortunately, electrophysiological parameters provide limitedaccuracy as those parameters involve measuring electric currents andcannot measure biological parameters such as hemodynamic response.

SUMMARY

Disclosed herein are methods and devices for measuring a state ofanesthesia in a noninvasive manner using functional near-infrared (fNIR)spectroscopy. For example, fNIR signals may be obtained and processed tomeasure deoxygenated hemoglobin (deoxy-Hb) and/or oxygenated hemoglobin(oxy-Hb) content. An active brain consumes oxygen transported to thebrain by oxy-Hb in the blood. As the oxy-Hb gives up oxygen, the oxy-Hbtransforms into deoxy-Hb. Oxy-Hb and deoxy-Hb have characteristicoptical properties in the visible and near-infrared (NIR) light range.Accordingly, fNIR may be used to measure concentrations of deoxy-Hband/or oxy-Hb as a measure of brain activity and the state ofanesthesia. As will be described below, optical techniques derived fromthe physical principles of light absorption and reflectance may be usedto detect changes in a neuromarker, such as changes in the hemodynamicresponse of the cortex. A neuromarker may provide an index ofanesthesia, correlating percentages of deoxy-HB to varying levels ofcortical activity.

According to an example embodiment, a device may determine the state ofanesthesia. The device may include of a light source for emitting nearinfrared (NIR) light at varying frequencies and/or wavelengths, and alight detector for receiving the NIR light. The light detector may beadapted for detecting concentrations of oxy-Hb and/or deoxy-Hb. A lightsource, for example, may be any light emitting source such as a lightemitting diode (LED), for example, and the light detector may be anydevice capable of receiving light, such as a photodetector, for example.

In another example embodiment, the state of anesthesia may be determinedby measuring an optical density change of NIR light. Two or morewavelengths of NIR light may be directed on a patient and an fNIR signalmay be received. The received fNIR signal may be used to measure anoptical density change of the NIR light. Using the optical densitychange, a deoxy-Hb concentration and/or an oxy-Hb concentration and/or atotal hemoglobin volume may be obtained. A percentage and/or rate ofchange of the deoxy-Hb concentration may then be used to determine astate of anesthesia. An amount of an anesthetic may then be administeredto either maintain or alter the state of anesthesia. An anesthetic maybe any chemical or drug that brings about a state of anesthesia. Inanother example embodiment, the state of anesthesia may be determined byremoving the effect of an artifact from the fNIR signal. An fNIR signalmay be emitted and received. A non-cortical signal that may beindicative of an artifact may be included within the received fNIRsignal and may be captured. Artifacts within the received fNIR signalmay have been caused by strong surgery room lighting, patient-tabletilting, patient intubation and extubation, or the like. These artifactsmay have an effect on the fNIR signals and may be identified and/orremoved by capturing the non-cortical signal indicative of the artifactand removing the non-cortical signal from the fNIR using a noise removalalgorithm. In selecting the noise removal algorithm, a switchingtechnique may be used to select the component analysis algorithm such asa principal component analysis (PCA), an independent component analysis(ICA), or the like. The selected noise removal algorithm may thensubtract a portion of the non-cortical signal from the fNIR signal. ThefNIR signal may be used to measure an optical density change of the NIRlight that may then be used to determine the state of anesthesia. Anamount of an anesthetic may then be administered to either maintain oralter the state of anesthesia.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter. Furthermore,the claimed subject matter is not limited to implementations that solveany or all disadvantages noted in any part of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example embodiment of a system that may be used todetermine a state of anesthesia.

FIG. 2 illustrates an example embodiment of a computing environment thatmay be used to determine a state of anesthesia.

FIGS. 3A, 3B illustrate example embodiments of devices for determining astate of anesthesia.

FIG. 4 illustrates a range of wavelengths that may be used to determinea state of anesthesia.

FIG. 5 illustrates an example embodiment of a device for determining astate of anesthesia.

FIG. 6 depicts a flow diagram of an example method for determining astate of anesthesia by measuring an optical density change of NIR light.

FIG. 7 illustrates deoxygenated hemoglobin concentrations that mayindicate a state of anesthesia.

FIG. 8 depicts a flow diagram of an example method for determining astate of anesthesia by removing the effect of an artifact from an fNIRsignal.

FIG. 9 depicts a flow diagram of an example method for removing theeffect of an artifact from an fNIR signal.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Disclosed herein are techniques that may be used for quantitativelyevaluating the depth of anesthesia in a noninvasive manner. For example,fNIR signals may be obtained and processed to measure deoxygenatedhemoglobin (deoxy-Hb) and/or oxygenated hemoglobin (oxy-Hb) content. Anactive brain consumes oxygen transported to the brain by oxy-Hb in theblood. As the oxy-Hb gives up oxygen, the oxy-Hb transforms intodeoxy-Hb. Oxy-Hb and deoxy-Hb have characteristic optical properties inthe visible and near-infrared light range. Accordingly, fNIR may be usedto measure concentrations of deoxy-Hb and/or oxy-Hb to measure of brainactivity and the state of anesthesia.

FIG. 1 illustrates an example embodiment of a system that may be used todetermine a state of anesthesia. In an example embodiment, the system 10may be used to determine and/or track a state of anesthesia of apatient, such as the patient 5.

As shown in FIG. 1 the system 10 may include a computing environment 12.The computing environment 12 may be a computing device such as acomputer, a personal digital assistant (PDA), a smartphone or the like.According to an example embodiment, the computing environment 12 mayinclude hardware components and/or software components such that thecomputing environment 12 may be used to execute applications such anoperating system, state of anesthesia monitoring software, or the like.In one embodiment, the computing environment 12 may include a processor,such as a standardized processor, a specialized processor, amicroprocessor, or the like, that may execute instructions including,for example, instructions for emitting an fNIR signal, receiving an fNIRsignal, determining a state of anesthesia, or any other suitableinstruction, which will be described in more detail below. In an exampleembodiment, the computing environment 12 may contain filters andamplifiers that may be used to power and control a capture device, suchas the capture device 20. The filters and amplifiers may be implementedin software, digital hardware, analog hardware, or a combination ofsoftware and hardware.

The system 10 may further include a capture device 20. The capturedevice 20 may be, for example, a device that may direct light at varyingwavelengths and receive an fNIR signal after it has passed through humantissue, such as the tissue of patient 5, as will be described in moredetail below. In another embodiment, which will also be described inmore detail below, the capture device 20 may further be used todetermine a state of anesthesia for a patient, such as patient 5. Thecapture device 20 may connected to the computing environment 12 via, forexample, via a coaxial cable, an Ethernet cable, an HDMI cable, a DVIcable, a VGA cable, or the like. In another example embodiment, thecapture device 20 may also be connected to the computing environment 12via a wireless network such as Bluetooth, Wi-Fi, IEEE 802.11, ZigBee, orthe like.

According to one embodiment, system 10 may be connected to anaudiovisual device 16 such as a television, a monitor, a high-definitiontelevision (HDTV), or the like that may provide visuals and/or audio forthe monitoring state of anesthesia. For example, the computingenvironment 12 may include a video adapter, such as a graphics card,and/or an audio adapter, such as a sound card, that may provideaudiovisual signals associated with the game application, non-gameapplication, or the like. The audiovisual device 16 may receive theaudiovisual signals from the computing environment 12 and may output thegame or application visuals and/or audio associated with the audiovisualsignals to the user 18. According to one embodiment, the audiovisualdevice 16 may be connected to the computing environment 12 via, forexample, an S-Video cable, a coaxial cable, an HDMI cable, a DVI cable,a VGA cable, or the like.

FIG. 2 illustrates an example embodiment of a computing environment 220that may be the computing environment 12 shown with respect to FIG. 1used to determine a state of anesthesia. The computing systemenvironment 220 is only one example of a suitable computing environmentand is not intended to suggest any limitation as to the scope of use orfunctionality of the presently disclosed subject matter. Neither shouldthe computing environment 12 be interpreted as having any dependency orrequirement relating to any one or combination of components illustratedin the exemplary operating environment 220. In some embodiments, thevarious depicted computing elements may include circuitry configured toinstantiate specific aspects of the present disclosure. For example, theterm circuitry used in the disclosure may include specialized hardwarecomponents configured to perform function(s) by firmware or switches. Inother examples embodiments the term circuitry may include ageneral-purpose processing unit, memory, etc., configured by softwareinstructions that embody logic operable to perform function(s). Inexample embodiments where circuitry includes a combination of hardwareand software, an implementer may write source code embodying logic andthe source code may be compiled into machine-readable code that may beprocessed by the general-purpose processing unit. Since one skilled inthe art may appreciate that the state of the art has evolved to a pointwhere there is little difference between hardware, software, or acombination of hardware/software, the selection of hardware versussoftware to effectuate specific functions is a design choice left to animplementer. More specifically, one of skill in the art may appreciatethat a software process may be transformed into an equivalent hardwarestructure, and a hardware structure may itself be transformed into anequivalent software process. Thus, the selection of a hardwareimplementation versus a software implementation is one of design choiceand left to the implementer.

In FIG. 2, the computing environment 220 comprises a computer 241, whichtypically includes a variety of computer readable media. Computerreadable media may be any available media that may be accessed bycomputer 241. Computer readable media includes both volatile andnonvolatile media, removable and non-removable media. The system memory222 includes computer storage media in the form of volatile and/ornonvolatile memory such as read only memory (ROM) 223 and random accessmemory (RAM) 260. A basic input/output system 224 (BIOS), including thebasic routines that help to transfer information between elements withincomputer 241, such as during start-up, is typically stored in ROM 223.RAM 260 typically includes data and/or program modules that areimmediately accessible to and/or presently being operated on byprocessing unit 259. By way of example, and not limitation, FIG. 2illustrates operating system 225, application programs 226, otherprogram modules 227, and program data 228.

The computer 241 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only.FIG. 2 illustrates a hard disk drive 238 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 239that reads from or writes to a removable, nonvolatile magnetic disk 254,and an optical disk drive 240 that reads from or writes to a removable,nonvolatile optical disk 253 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that may be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 238 is typically connectedto the system bus 221 through an non-removable memory interface such asinterface 234, and magnetic disk drive 239 and optical disk drive 240are typically connected to the system bus 221 by a removable memoryinterface, such as interface 235.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 2, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 241. In FIG. 2, for example, hard disk drive 238 is illustratedas storing operating system 258, application programs 226, other programmodules 227, and program data 228. Note that these components may eitherbe the same as or different from operating system 225, applicationprograms 226, other program modules 227, and program data 228. Operatingsystem 225, application programs 226, other program modules 227, andprogram data 228 are given different numbers here to illustrate that at,a minimum, they are different copies. A user may enter commands andinformation into the computer 241 through input devices such as akeyboard 251 and pointing device 252, commonly referred to as a mouse,trackball or touch pad. Other input devices (not shown) may include amicrophone, joystick, game pad, satellite dish, scanner, or the like.These and other input devices are often connected to the processing unit259 through a user input interface 236 that is coupled to the systembus, but may be connected by other interface and bus structures, such asa parallel port, game port or a universal serial bus (USB). The capturedevice 20, as shown in FIGS. 1-3B, may define an additional inputdevice. A monitor 242 or other type of display device is also connectedto the system bus 221 via an interface, such as a video interface 232.In addition to the monitor, computers may also include other peripheraloutput devices such as speakers 244 and printer 243, which may beconnected through a output peripheral interface 233.

The computer 241 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer246. The remote computer 246 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 241, although only a memory storage device 247 has beenillustrated in FIG. 2. The logical connections depicted in FIG. 2include a local area network (LAN) 245 and a wide area network (WAN)249, but may also include other networks. Such networking environmentsare commonplace in offices, enterprise-wide computer networks, intranetsand the Internet.

When used in a LAN networking environment, the computer 241 is connectedto the LAN 245 through a network interface or adapter 237. When used ina WAN networking environment, the computer 241 typically includes amodem 250 or other means for establishing communications over the WAN249, such as the Internet. The modem 250, which may be internal orexternal, may be connected to the system bus 221 via the user inputinterface 236, or other appropriate mechanism. In a networkedenvironment, program modules depicted relative to the computer 241, orportions thereof, may be stored in the remote memory storage device. Byway of example, and not limitation, FIG. 2 illustrates remoteapplication programs 248 as residing on memory device 247. It will beappreciated that the network connections shown are exemplary and othermeans of establishing a communications link between the computers may beused.

FIG. 3A illustrates an example embodiment of a device 300 fordetermining a state of anesthesia. The example device may be the capturedevice 20 with respect to FIG. 1-3B. The capture device may be used, forexample, with the computing device 12 of the system 10, described withrespect to FIG. 1, to determine a state of anesthesia of a patient, suchas the patient 5.

In one example embodiment, the device 300 may contain a light source,such as the light source 310. The light source 310 may be a lightemitting diode, an incandescent light bulb, a cathode ray tube, or thelike. The light source may emit NIR light at varying wavelengths. Forexample, the light source may emit NIR the light that may mostlyabsorbed by oxy-Hb and/or deoxy-H-lb.

As shown in FIG. 4, in one embodiment, the light source may emit lightin the NIR range between 700-900 nm. In this range, water, a majorcomponent of most tissues, may absorb very little energy while thespectra of oxy-Hb and deoxy-Hb may be distinct enough to allowspectroscopy and measures of separate concentrations of both oxy-Hb anddeoxy-Hb molecules.

Returning to FIG. 3A, in another embodiment, the light source may emittwo or more wavelengths of the NIR light in a range between 700 nm and900 nm. For example, the light source may emit a first wavelength of 730nm and a second wavelength of 850 nm. The two or more wavelengths of theNIR light may be absorbed by the deoxy-Hb or the oxy-Hb.

As shown in FIG. 5, the light source 310 may emit NIR light at or near apatient's scalp and may pass through layers of tissue. For example, thelight source may be directed at a prefrontal cortex of a patient. TheNIR light may be absorbed and scattered by the oxy-Hb and deoxy-Hb. Apredictable quantity of photons may follow a ‘banana-shaped’ path andleave the tissue and may be measured using photodetectors, such as thelight detector 330, as will be described below.

Returning to FIG. 3A, in another embodiment, the light source may emittwo or more wavelengths of the NIR light in a range between 700 nm and900 nm. For example, the light source may emit a first wavelength of 730nm and a second wavelength of 850 nm. The two or more wavelengths of theNIR light may be absorbed by the deoxy-Hb or the oxy-Hb.

In another example embodiment, the device 300 may contain a lightdetector, such as the light detector 330. The light detector 330 may bea photodetector, a sensor, or the like. The light detector may captureand/or receive an fNIR signal in response to directing the wavelengthsof NIR light on the patient, emitted by the light source 310. Forexample, the light detector may receive the fNIR signal after the fNIRsignal has passed through human tissue. To assist the light detector 330in receiving NIR light, the light detector may be placed a distance,such as 2.5 cm or 3 cm, away from the light source. This distance mayenable the light detector 320 to receive NIR light that may travel alonga banana shaped path between the light source 320 and the light detector330. The light detector 330 may be used to measure a portion of the NTRlight that may not absorbed by human tissue. In another exampleembodiment, the light detector 330 may be adapted to detect a relativechange in the percentage of deoxy-Hb in a total blood volume, as will befurther described below.

In another example embodiment, the light detector 330 may receive NIRlight that may contain non-cortical signals and/or artifacts may bereceived. The received NIR light may contain various wavelengths of fNIRsignals that were emitted by a device, such as the device 300. Forexample, the light detector may receive NIR light that has passedthrough human tissue. The received NIR light may contain a non-corticalsignal that may indicative of an artifact. Artifacts within the receivedNIR light may have been caused by strong surgery room lighting,patient-table tilting, patient intubation and extubation, or the like.These artifacts may affect the NIR light.

The device 300 may include a flexible circuit, such as the flexiblecircuit 320. The flexible circuit 320 may be a disposable single-usecushioning material that may attach to the patient's forehead. Theflexible circuit 320 may provide a reliable integrated wiring solutionand consistent component spacing. The flexible circuit 320 may enablethe device 300 to adapt to the various contours of the patient's head.For example, the flexible circuit 320 may allow the device 300 to beplaced in such a way that the light detectors are able to maintain anorthogonal orientation to the skin surface. This orientation maydramatically improving light coupling efficiency and signal strength.

FIG. 3B illustrates an additional example embodiment a device 300 fordetermining a state of anesthesia. The device 300 may include a lightdetector, such as the light detector 340, that may be used to capture areference signal. This reference signal may be used to remove noise fromthe fNIR signals that may be used to measure oxy-Hb and/or deoxy-Hb. Forexample, the reference signal may be emitted to capture non-corticalsignals during a period of minimal activation. These non-corticalsignals may be used to calibrate and/or remove noise from the otherreceived fNIR signals light. In one example embodiment, the lightdetector 340 may be placed at a distance from the light source 310 thatdiffers from the distance between light detector 330 and the lightsource 310.

In another example embodiment, the light detector 340 may receive NIRlight that may contain non-cortical signals and/or artifacts may bereceived. The received NIR light may contain various wavelengths of NIRlight emitted by a device such as the device 300. For example, the lightdetector 340 may receive NIR light that has passed through human tissue.The received NIR light may contain a non-cortical signal that may beindicative of an artifact. Artifacts within the received fNIR signal mayhave been caused by strong surgery room lighting, patient-table tilting,patient intubation and extubation, or the like. These artifacts mayaffect the NIR light.

FIG. 6 depicts a flow diagram of an example method for determining astate of anesthesia by measuring an optical density change of NIR light.The example method may be implemented using, for example, the device 20and/or the computing device 220 of the system 10 described with respectto FIGS. 1-3. In an example embodiment, the method may take the form ofprogram code (i.e., instructions) that may be executed by, for example,the capture device 20 and/or the computing environment 12 of the system10 described with respect to FIG. 1-3.

According to an example embodiment, at 605, NIR light may be directed ona patient, such as the patient 5 shown with respect to FIG. 1. The NIRlight may be directed by a light emitting diode, an incandescent lightbulb, a cathode ray tube, or the like. The directed NIR light may be atvarying wavelengths and may have the same characteristic opticalproperties as oxy-Hb and deoxy-Hb.

In one example embodiment, two or more wavelengths of NIR light in arange between 700 nm and 900 nm may be directed on a patient. Forexample, the light source may emit a first wavelength of 730 nm and asecond wavelength of 850 nm. The two or more wavelengths of the NIRlight may be absorbed by the deoxy-Hb or the oxy-Hb.

In another example embodiment, the NIR light may be directed at afrontal cortex of the patient. For example, the fNIR may be directed ator near a patient's scalp. The fNIR may pass through layers of tissueand may be absorbed and scattered by the oxy-Hb and deoxy-Hb. As shownin FIG. 5, a predictable quantity of NIR light may follow a‘banana-shaped’ path and leave the tissue.

Referring back to FIG. 6, at 610, NIR light may be received. The NIRlight may be captured and/or received at varying frequencies and/orwavelengths. For example, NIR light at a wavelength of 730 nm may bereceived. In one embodiment, the device 300 may have emitted thereceived NIR light. In another embodiment, the received NIR light mayhave passed through human tissue.

At 615, an optical density change of the fNIR signal may be measured toobtain a deoxy-Hb concentration and/or relative to an oxy-Hbconcentration. In one embodiment, the optical density change may bemeasured by determining the amount of NIR light that undergoesabsorption and scattering by tissue. For example, under the modifiedBeer-Lambert Law the optical density after absorption and scattering ofthe biological tissue may be measured by using the equation:

I=GI _(o) e ^(−(α) _(HB) ^(C) _(HB) ^(+α) _(HBO2) ^(C) _(HBO2) ^()*L)

In the above equation G may be a factor that accounts for themeasurement geometry and may be assumed constant when concentrationchanges. I_(o) is input light intensity, α_(HB) and α_(HBO2) are themolar extinction coefficients of deoxy-Hb and oxy-Hb. C_(HB) andC_(HBO2) are the concentrations of deoxy-Hb and oxy-Hb respectively, andL is the photon path which is a function of absorption and scatteringcoefficients μ_(a) and μ_(b). By measuring optical density changes attwo wavelengths, the relative change of deoxy-Hb and oxy-Hb versus timemay be obtained. For example, if the intensity measurement at an initialtime is I_(b) (baseline), and at another time is I, the optical densitychange due to variation in concentrations of deoxy-Hb and oxy-Hb duringthat period is:

${\Delta \; {OD}} = {{\log_{10}\frac{I_{b}}{I}} = {{\alpha_{HB}\Delta \; C_{HB}} + {\alpha_{{HBO}_{2}}\Delta \; C_{{HBO}_{2}}}}}$

In an another example embodiment, measuring the optical density changeof the NIR light may comprise measuring an absorption of each of the twoor more wavelengths of the NIR light after directing the fNIR on thepatient. For example, absorbance and/or scattering changes at two ormore wavelengths may be measured. One of the wavelengths used may bemore sensitive to oxy-Hb than to deoxy-Hb. Changes in the relativeconcentration of these oxy-Hb and deoxy-Hb may then be calculated usingthe two ore more wavelengths.

In another example embodiment, a baseline deoxy-Hb may be calculated bymeasuring the optical density change of the fNIR. In calculating thebaseline deoxy-Hb, the fNIR signal may be obtained prior toadministering anesthesia. For example, the baseline fNIR may bedetermined 20 seconds before administering anesthesia. This may beperformed to provide an understanding of the deoxy-Hb and/or oxy-Hblevels on a patient-by-patient basis before anesthesia may beadministered. The baseline fNIR may represent the deoxy-Hb concentrationlevels, or may be a ratio, such as a ratio of deoxy-Hb to oxy-Hb, or thelike.

In another example embodiment, a percentage of deoxy-Hb concentrationmay be a ratio of the deoxy-Hb to at least one of an oxy-Hbconcentration, a baseline deoxy-Hb, or a total hemoglobin volume.Measurements may be performed at two or more different wavelengths andmay allow for the calculation of changes in concentrations of deoxy-Hb(ΔC_(HB)) and oxy-Hb (ΔC_(HBO) ₂ ). Change in oxygenation and bloodvolume or total hemoglobin (Hbt) may then be deduced using the followingequation:

Oxygenation=ΔC _(HBO) ₂ −ΔC _(HB)

The percentage of deoxy-Hb concentration may then be calculated as aratio of the deoxy-Hb to at least one of an oxy-Hb concentration, abaseline deoxy-Hb, or a total hemoglobin volume. In one exampleembodiment, the percentage and/or ratio of deoxy-Hb may be measured at asample rate, such as a 2 Hz sample rate, and may be measured in realtime.

At 620, a percentage and/or rate of change of the deoxy-Hb concentrationmay be correlated to determine the state of anesthesia. Anesthetics mayhave direct cerebral vasodilatory effects and may increase cerebralblood flow. Increases in cerebral blood flow are generally followed byincreases in cerebral blood volume. The increases in cerebral bloodvolume may cause excessive amount of Hbt, oxy-Hb and deoxy-Hb duringdeep anesthesia and may be caused by a combination of the decrease inneuronal metabolic demand coupled with an increase in cerebral bloodfloor.

In one example embodiment, the decreases in percentage and/or rate ofdeoxy-Hb changes during deep anesthesia may be monitored and correlatedto the cerebral metabolic rate (demand) suppression by the administeredanesthetic agents. For example, as shown in FIG. 7, Deoxy-Hbconcentration may indicate a changing state of anesthesia as lightanesthesia may be associated with relatively less deoxy-Hb concentrationthan deep anesthesia. Additionally, a change, such as a decrease, in thepercentage of deoxy-Hb may be an indication of changing levels ofcortical activity, such as increased cortical activity, and/or anemergence from anesthesia. For example, deoxy-Hb averages maydemonstrate a very slow rate of change in deep anesthesia, whereas thisrate of change may be drastically increased when the patient emerges towakefulness. A neuromarker may provide an index of anesthesia thatcorrelates levels of cortical activity to the varying states ofanesthesia. For example, the neuromarker may indicate a percentage ofdeoxy-HB or a percentage range of deoxy-HB to a level of conicalactivity that correlates to a deep state of anesthesia. Returning toFIG. 6, in one embodiment, cortical activity may correspond to at leastone of a state of anesthesia, a transition between states of anesthesia,or a risk level that corresponds to an emergence from anesthesia. Theneuromarker may indicate the state of anesthesia or a changing state ofanesthesia by identifying the rate of change in cortical activity. Forexample, a slow rate of change in the percentage of deoxy-HB may be anindication of a deep state of anesthesia. The neuromarker may beextracted from fNIR measurements particular to a single patient or basedon a collection of data from multiple patients.

In another example embodiment, the state of anesthesia may be determinedby comparing the percentage of deoxy-Hb to the baseline deoxy-Hb. Thebaseline deoxy-Hb may indicate the deoxy-Hb concentration and/or ratiothat may exist in a patient prior to the administration of anesthesiaand may indicate the deoxy-Hb levels that correlate to a state ofawareness. After anesthesia is administered, a deoxy-Hb percentageand/or rate may be calculated. The deoxy-Hb percentage and/or rate maythen be compared to the baseline deoxy-Hb to determine the state ofanesthesia. For example, a deoxy-Hb concentration that is higher thanthe baseline deoxy-Hb concentration may indicate that the state ofanesthesia is deep or light anesthesia.

In one example embodiment, a state of anesthesia may be described interms of intraoperative data such as times of anesthetic induction,first surgical incision, and wound closure as well as administration ofmedication. In another example embodiment, a state of anesthesia may bedescribed in terms of the amount of brain activity desired during aphased of a procedure. For example, the state of anesthesia may be adeep state of anesthesia defined as the four-minute time interval priorto wound closure, or a light state of anesthesia defined as thefour-minute time interval prior to eye opening. The state of anesthesiamay also be an emergence state of anesthesia defined as any timeinterval where the anesthetic agents may not prevent patient awareness.

At 625, an amount of an anesthetic to administer may be determined. Inone embodiment, the amount of anesthesia may be determined according tothe state of anesthesia. For example, if the state of anesthesiaindicates patient awareness, an amount of an anesthetic may beadministered to prevent awareness. In another example embodiment, thelevels of deoxy-Hb may be used to administer the minimal dose ofanesthetic required to achieve the desired depth of anesthesia. Forexample, by monitoring the levels of deoxy-Hb, the effectiveness ofanesthesia on a patient may be determined. Upon determining theeffectiveness of anesthesia, a dosage of anesthesia may be provided toalter the levels of deoxy-Hb and to achieve the desired depth ofanesthesia. The administration of anesthesia may include intravenousdrug doses, such as Fentanyl. Propofol, or the like, and inhalationaldrugs, such as Sevoflurane, Desflurane, or the like.

FIG. 8 depicts a flow diagram of an example method for determining astate of anesthesia by removing the effect of an artifact from the fNIRsignal. The example method may be implemented using, for example, thedevice 20 and/or the computing device 220 of the system 10 describedwith respect to FIGS. 1-3. In an example embodiment, the method may takethe form of program code (i.e., instructions) that may be executed by,for example, the capture device 20 and/or the computing environment 12of the system 10 described with respect to FIG. 1-3.

According to an example embodiment, at 805, fNIR signals may be emitted.The fNIR signals may be emitted by a light emitting diode, anincandescent light bulb, a cathode ray tube, or the like. The fNIRsignals emitted may comprise varying frequencies and/or wavelengths andmay have the same characteristic optical properties as oxy-Hb anddeoxy-Hb.

In one example embodiment, two or more wavelengths of fNIR signals in arange between 700 nm and 900 nm may be emitted. For example, a firstwavelength of 730 nm and a second wavelength of 850 nm may be emitted.The two or more wavelengths of the fNIR signals may be absorbed by thedeoxy-Hb or the oxy-Hb.

In another example embodiment, the fNIR signal may include at leastthree wavelengths. In one embodiment, at least one wavelength may be notemitted, for example utilized at dark-current condition, to capture areference signal. This reference signal may be used to remove noise fromthe fNIR signals that may be used to measure oxy-Hb and/or deoxy-Hb. Forexample, the reference signal may only capture non-cortical signalsduring a period of no-emitting light condition, which may be known asdark current condition. These non-cortical signals may then be used tocalibrate and/or remove noise from the other emitted signals.

In another example embodiment, the fNIR signal may be emitted at afrontal cortex of the patient. For example, the fNIR signal may beemitted at or near a patient's scalp. The fNIR signal may pass throughlayers of tissue and may be absorbed and scattered by the oxy-Hb anddeoxy-Hb. As shown in FIG. 5, a predictable quantity of fNIR signal mayfollow a banana-shaped path and leave the tissue.

Referring back to FIG. 8, at 810, an fNIR signal that may containnon-cortical signals and/or artifacts may be received. The received fNIRsignal may contain various wavelengths of fNIR signals emitted by adevice, such as the device 300. For example, the fNIR signal may bereceived after the fNIR signal has passed through human tissue. Thereceived fNIR signal may also contain a non-cortical signal that may beindicative of an artifact. Artifacts within the received fNIR signal mayhave been caused by strong surgery room lighting, patient-table tilting,patient intubation and extubation, or the like. These artifacts may havean effect on the fNIR signal.

At 815, a switching technique may be used to select the componentanalysis algorithm such as a principal component analysis (PCA), anindependent component analysis (ICA), or the like. Artifacts signals maybe identified and/or removed by capturing the non-cortical signalindicative of the artifact and removing the non-cortical signal from thefNIR using a component analysis algorithm. In selecting the componentanalysis algorithm, a switching technique may be used to select thecomponent analysis algorithm that performs better.

For example, FIG. 9 demonstrates that for each wavelength measurementeither at 730 nm or 850 nm, a separate ICA and PCA algorithm may beperformed where the measurement vector x(t) may be a two dimensionalcontaining the measurement obtained either at 730 or at 850 nm and theone at the reference signal The unknown independent/uncorrelated sourcesignals s(t) that may be estimated by the ICA/PCA algorithm may also betwo dimensional which will be the non-physiological noise signal and theclean raw intensity signal related with hemodynamic changes due tocognitive activity. Once the unknown A matrix and the unknown sourcesignals s(t) are extracted, the noise signal may be selected bycorrelating the independent components with the reference signalseparately and selecting the one analysis giving the highestcorrelation.

In an example embodiment, the reference signal may be received inresponse to absence of light emitting during a period of dark currentcondition. The reference signal may be obtained in the environment inwhich the patient will be anesthetized prior to activity in theenvironment. For example, the reference signal may be received prior toactivity that causes a hemodynamic response, such as patient movement,lighting, extubation, intubation, or the like. The lights may be minimalor off during receipt of the reference signal.

Returning to FIG. 8, at 820, the effect of an artifact may be removedfrom the fNIR signal. In one embodiment, the selected component analysisalgorithm may be used to remove the effect of the artifact from the fNIRsignal by subtracting a portion of the non-cortical signal from the fNIRsignal.

For example, FIG. 9 demonstrates that after the independent componentcorresponding to the noise signal has been selected, the noise may beremoved from the original 730 nm or 850 nm recordings by subtracting itfrom that measurement with an appropriate amount, such as the amount theestimated A matrix described above. Correlation between the referencesignal measurement and the noise removed intensity measurements via ICAand PCA algorithms are calculated separately. The outcome of the bestperforming algorithm that generates lowest correlation may be selectedas the cleaned raw intensity measurement.

Returning to FIG. 8, at 825, an optical density change of the fNIRsignal may be measured to obtain a deoxy-Hb concentration and/or to anoxy-Hb concentration. In one embodiment, the optical density change maybe measured by determining the amount of fNIR signal that undergoesabsorption and/or scattering by tissue. For example, under the modifiedBeer-Lambert Law the optical density after absorption and scattering ofthe biological tissue may be measured by using the equation:

I=GI _(o) e ^(−(α) _(HB) ^(C) _(HB) ^(+α) _(HBO2) ^(C) _(HBO2) ^()*L)

In the above equation G may be a factor that accounts for themeasurement geometry and may be assumed constant when concentrationchanges. I_(o) is input light intensity. α_(HB) and α_(HBO2) are themolar extinction coefficients of deoxy-Hb and oxy-Hb, C_(HB) andC_(HBO2) are the concentrations of deoxy-Hb and oxy-Hb, respectively andL is the photon path which is a function of absorption and scatteringcoefficients μ_(a) and μ_(b). By measuring optical density changes attwo wavelengths, the relative change of deoxy-Hb and oxy-Hb versus timemay be obtained. For example, if the intensity measurement at an initialtime is I_(b) (baseline), and at another time is I, the optical densitychange due to variation in concentrations of deoxy-Hb and oxy-Hb duringthat period is:

${\Delta \; {OD}} = {{\log_{10}\frac{I_{b}}{I}} = {{\alpha_{HB}\Delta \; C_{HB}} + {\alpha_{{HBO}_{2}}\Delta \; C_{{HBO}_{2}}}}}$

In an another example embodiment, measuring the optical density changeof the fNIR signal may comprise measuring an absorption of each of thetwo or more wavelengths of the fNIR signal after directing the fNIRsignal on the patient. For example, absorbance and/or scattering changesat two or more wavelengths may be measured. One of the wavelengths usedmay be more sensitive to oxy-Hb than to deoxy-Hb. Changes in therelative concentration of these oxy-Hb and deoxy-Hb may then becalculated using the two ore more wavelengths.

In another example embodiment, a baseline deoxy-HI-b may be calculatedby measuring the optical density change of the fNIR signal. Incalculating the baseline deoxy-Hb, the fNIR signal may be obtained priorto an administration of anesthesia. For example, the baseline fNIR maybe determined 20 seconds before the administration of anesthesia. Thismay be performed to provide an understanding of the deoxy-Hb levels inon a patient-by-patient basis before anesthesia may be administered.

In another example embodiment, a percentage of deoxy-Hb concentrationmay be a ratio of the deoxy-Hb to at least one of an oxy-Hbconcentration, a baseline deoxy-Hb, or a total hemoglobin volume.Measurements may be performed at two or more different wavelengths andmay allow for the calculation of allow the calculation of changes inconcentrations of deoxy-Hb (ΔC_(HB)) and oxy-Hb (ΔC_(HBO2)). Change inoxygenation and blood volume or total hemoglobin (Hbt) may then bededuced using the following equation:

Oxygenation=ΔC _(HBO) ₂ −ΔC _(HB)

The percentage of deoxy-Hb concentration may then be calculated as aratio of the deoxy-Hb to at least one of an oxy-Hb concentration, abaseline deoxy-Hb, or a total hemoglobin volume. In one exampleembodiment, the percentage of deoxy-Hb may be measured at a sample rate,such as a 2 Hz sample rate, and may be measured in real time.

At 830, the state of anesthesia may be determined. In one embodiment, apercentage and/or rate of change of the deoxy-Hb concentration may becorrelated to determine the state of anesthesia. Anesthetics may havedirect cerebral vasodilatory effects and may increase cerebral bloodflow. Increases in cerebral blood flow are generally followed byincreases in cerebral blood volume. The increases in cerebral bloodvolume may cause excessive amount of total hemoglobin (Hbt), oxy-Hb anddeoxy-Hb during deep anesthesia and may be caused by a combination ofthe decrease in neuronal metabolic demand coupled with an increase incerebral blood flow.

In one example embodiment, the decreases in percentage and/or rate ofdeoxy-Hb changes during deep anesthesia may be monitored and correlatedto the cerebral metabolic rate (demand) suppression by the administeredanesthetic agents. For example, as shown in FIG. 7, Deoxy-Hbconcentration may indicate a changing state of anesthesia as lightanesthesia may be associated with relatively less deoxy-Hb concentrationthan deep anesthesia. Additionally, a change, such as a decrease, in thepercentage of deoxy-Hb may be an indication of changing levels ofcortical activity, such as increased conical activity, and/or anemergence from anesthesia. For example, deoxy-Hb averages maydemonstrate a very slow rate of change in deep anesthesia, whereas thisrate of change may be drastically increased when the patient emerges towakefulness. Returning to FIG. 6, in one embodiment, cortical activitymay correspond to at least one of a state of anesthesia, a transitionbetween states of anesthesia, or a risk level that corresponds to anemergence from anesthesia.

In another example embodiment, the state of anesthesia may be determinedby comparing the percentage of deoxy-Hb to the baseline deoxy-Hb. Thebaseline deoxy-Hb may indicate the deoxy-Hb concentration and/or ratiothat may exist in a patient prior to the administration of anesthesiaand may indicate the deoxy-Hb levels that correlate to a state ofawareness. After anesthesia is administered, a deoxy-Hb percentageand/or rate may be calculated. The deoxy-Hb percentage and/or rate maythen be compared to the baseline deoxy-Hb to determine the state ofanesthesia. For example, a deoxy-Hb concentration that is higher thanthe baseline deoxy-Hb concentration may indicate that the state ofanesthesia is deep or light state.

In one example embodiment, a state of anesthesia may be at described interms intraoperative data that such as times of anesthetic induction,first surgical incision, and wound closure as well as administration ofmedication. In another example embodiment, a state of anesthesia may bedescribed in terms of the desired amount of patient brain activityduring a phase of a procedure. For example, the state of anesthesia maybe the deep state of anesthesia defined as the four-minute time intervalprior to wound closure, or the light state of anesthesia defined as thefour-minute time interval prior to eye opening. The state of anesthesiamay also be emergence state of anesthesia defined as any time intervalwhere the anesthetic agents no longer prevent patient awareness.

At 835, an amount of an anesthetic to administer may be determined. Inone embodiment, the amount of anesthesia may be determined according tothe state of anesthesia. For example, if the state of anesthesiaindicates patient awareness, an amount of an anesthetic may beadministered prevent awareness. In another example embodiment, thelevels of deoxy-Hb may be used to administer the minimal dose ofanesthetic required to achieve the desired depth of anesthesia. Forexample, by monitoring the levels of deoxy-Hb, the effectiveness ofanesthesia on a patient may be determined. Upon determining theeffectiveness of anesthesia, a dosage of anesthesia may be provided tochange the levels of deoxy-Hb and achieve the desired depth ofanesthesia. The administration of anesthesia may include intravenousdrug doses, such as Fentanyl, Propofol, or the like, and inhalationaldrugs, such as Sevoflurane. Desflurane, or the like.

FIG. 9 depicts a flow diagram of an example method for removing theeffect of an artifact from an fNIR signal. The example method may beimplemented using, for example, the device 20 and/or the computingdevice 220 of the system 10 described with respect to FIGS. 1-3. In anexample embodiment, the method may take the form of program code (i.e.,instructions) that may be executed by, for example, the capture device20 and/or the computing environment 12 of the system 10 described withrespect to FIG. 1-3.

According to an example embodiment, at 905, a 730 nm fNIR signal, an 850nm fNIR signal, and reference fNIR signal may be received and/oracquired. The reference signal may be used to remove noise from the 730nm and 850 nm fNIR signals that may be used to measure oxy-Hb and/ordeoxy-Hb. For example, the reference signal may be emitted to capturenon-cortical signals during a period of minimal activation. Thesenon-cortical signals may then be used to calibrate and/or remove noisefrom the other emitted signals.

In another example embodiment, the 730 nm, the 850 nm, and the referencefNIR signals may be received at a location near the frontal cortex ofthe patient. For example, the fNIR signal may be emitted at or near apatient's scalp. The fNIR signal may pass through layers of tissue andmay be absorbed and scattered by the oxy-Hb and deoxy-Hb. As shown inFIG. 5, a predictable quantity of fNIR signal may follow a banana-shapedpath and leave the tissue.

Referring back to FIG. 9, at 910, a signal level and correlation checkmay be performed. Calculations for hemodynamic signals may be carriedout using the measurements obtained for the 730 nm and 850 nm fNIRsignal. In one embodiment, a signal level check may be performed todetermine the signal strength of the 730 nm, 850 nm, and reference NIRlight. If a weak signal is detected, an adjustment may be made tostrengthen the signal.

At 915, a dark current measurement may be taken to determine whether acomponent analysis algorithm may be employed. A dark current measurementmay be a measurement taken when NIR light is not being emitted. The darkcurrent measurement may be used to determine whether non-corticalsignals may be received. This may be done to ensure that componentanalysis may be performed when non-cortical signals may affect the fNIRsignals.

At 920, in one example embodiment, a switching technique may be used toselect the component analysis algorithm such as a principal componentanalysis (PCA), an independent component analysis (ICA), or the like.Artifacts signals may be identified and/or removed by capturing thenon-cortical signal indicative of the artifact and removing thenon-cortical signal from the fNIR using a component analysis algorithm.In selecting the component analysis algorithm, a switching technique maybe used to select the component analysis algorithm that performs better.

For example, for each wavelength measurement either at 730 nm or 850 nm,a separate ICA and PCA algorithm may be performed where the measurementvector x(t) may be a two dimensional containing the measurement obtainedeither at 730 or at 850 nm and the one at the reference signal. Theunknown independent/uncorrelated source signals s(t) that may beestimated by the ICA/PCA algorithm may also be two dimensional whichwill be the non-physiological noise signal and the clean raw intensitysignal related with hemodynamic changes due to cognitive activity. Oncethe unknown A matrix and the unknown source signals s(t) are extracted,the noise signal may be selected by correlating the independentcomponents with the reference signal separately and selecting the oneanalysis giving the highest correlation, such as a correlation above0.7.

At 930, the selected component analysis algorithm may be applied to the730 nm fNIR signal and/or the 850 nm fNIR signal.

At 935, the effect of an artifact may be removed from the fNIR signaland/or ignored. In one embodiment, the selected component analysisalgorithm may be used to remove the effect of the artifact from the fNIRsignal by subtracting a portion of the non-cortical signal from the fNIRsignal. For example, after the independent component corresponding tothe noise signal has been selected, the noise may be removed from theoriginal 730 nm or 850 nm recordings by subtracting it from thatmeasurement with an appropriate amount, such as the amount the estimatedA matrix described previously. Correlation between the reference signalmeasurement and the noise removed intensity measurements via ICA and PCAalgorithms are calculated separately. The outcome of the best performingalgorithm that generates lowest correlation may be selected as thecleaned raw intensity measurement.

In one embodiment, a component analysis algorithm may not used.Non-cortical signals may not be detected in the 730 nm, 850 nm, orreference fNIR signals

What is claimed:
 1. A method for using a functional near-infrared signal to correlate to a state of anesthesia, the method comprising: receiving the functional near-infrared signal in response to directing wavelengths of light in a near-infrared range on a patient; determining, from the functional near-infrared signal, a relative deoxyhemoglobin concentration and oxyhemoglobin concentration; and correlating the percentage of the deoxyhemoglobin concentration to the state of anesthesia.
 2. The method of claim 1, wherein the functional near-infrared signal is indicative of a change in the light at each of the wavelengths.
 3. The method of claim 2, wherein the change in the light at each of the wavelengths is due to at least one of reflection or an absorption of the light by tissue of the patient.
 4. The method of claim 2, further comprising measuring the change in the light at each of the wavelengths.
 5. The method of claim 4, wherein the change measured in the light is at least one of an optical density change or a light intensity change.
 6. The method of claim 1, further comprising determining a total hemoglobin volume.
 7. The method of claim 1, wherein the percentage of the deoxyhemoglobin concentration is a ratio of the deoxyhemoglobin concentration to at least one of the oxyhemoglobin concentration, a baseline deoxyhemoglobin concentration, or a total hemoglobin volume.
 8. The method of claim 1, wherein a change in the percentage of deoxyhemoblogin is an indication of a changing level of cortical activity.
 9. The method of claim 1, wherein a decrease in the percentage of deoxyhemoglobin is an indication of increased cortical activity.
 10. The method of claim 1, wherein a change in the percentage of deoxyhemoblogin concentration is an indication of a changing state of anesthesia.
 11. The method of claim 1, further comprising measuring a rate of change in the percentage of deoxyhemoglobin by comparing the change in the light at each of the wavelengths at different times.
 12. The method of claim 11, wherein the rate of change is indicative of the state of anesthesia.
 13. The method of claim 12, wherein a slow rate of change in the deoxyhemoglobin is indicative of a deep state of anesthesia.
 14. The method of claim 12, wherein the rate of change is an indication of a changing state of anesthesia.
 15. The method of claim 11, wherein the change in the light at each of the wavelengths is measured at a sample rate of 2 Hz.
 16. The method of claim 1, wherein the state of anesthesia may be at least one of a deep state, a light state, or an emergence from anesthesia.
 17. The method of claim 1, wherein a decrease in the percentage of deoxyhemoglobin indicates an emergence from anesthesia.
 18. The method of claim 17, wherein the emergence from anesthesia is not identifiable from visual observation of the patient.
 19. The method of claim 1, wherein a baseline functional near-infrared signal is obtained prior to an administration of anesthesia indicative of a baseline deoxyhemoglobin percentage.
 20. The method of claim 19, wherein determining the state of anesthesia comprises comparing the percentage of deoxyhemoglobin to the baseline deoxyhemoglobin percentage.
 21. The method of claim 19, where the baseline functional near-infrared signal is obtained about 20 seconds before the administration of anesthesia.
 22. The method of claim 19, wherein the baseline functional near-infrared signal is indicative of the baseline deoxyhemoglobin percentage is obtained on a patient-by-patient basis.
 23. The method of claim 1, wherein the change in the light is measured in accordance with Beer-Lambert law.
 24. The method of claim 1, wherein the wavelengths comprise two wavelengths of light, each in a range between 700 nm and 900 nm.
 25. The method of claim 1, wherein a first wavelength is substantially absorbed by deoxyhemoglobin and a second wavelength is substantially absorbed by oxyhemoglobin.
 26. The method of claim 25, wherein the first wavelength is 730 nm and the second wavelength is 850 nm.
 27. The method of claim 1, further comprising directing the wavelengths of light in the near-infrared range on the patient.
 28. The method of claim 27, wherein the near-infrared light is directed at a prefrontal cortex of the patient.
 29. The method of claim 27, wherein the near-infrared light is directed to pass through human tissue.
 30. The method of claim 27, wherein the wavelengths of light are directed on the patient after an administration of anesthesia.
 31. The method of claim 30, wherein the administration of anesthesia comprises administering an amount of anesthetic to the patient.
 32. The method of claim 31, wherein the percentage of deoxyhemoglobin provides an indication of the amount of anesthetic to be administered.
 33. The method of claim 1, further comprising subtracting an effect of non-cortical signals on the functional near-infrared signal.
 34. The method of claim 1, wherein the percentage of deoxyhemoglobin is measured in real-time.
 35. The method of claim 1, further comprising comparing the percentage of deoxyhemoblogin concentration to a neuromarker that indicates a percentage of deoxyhemoglobin that corresponds to a level of cortical activity.
 36. The method of claim 35, wherein the level of cortical activity corresponds to at least one of the state of anesthesia, a transition between states of anesthesia, or a risk level that corresponds to an emergence from anesthesia.
 37. An functional near-infrared device for determining a state of anesthesia, the device comprising: a light detector for receiving a functional near-infrared signal indicative of a change in light in response to directing wavelengths of light on a patient; and a processor for determining, from the functional near-infrared signal, a relative deoxyhemoglobin concentration and oxyhemoglobin concentration, and correlating the percentage of the deoxyhemoglobin concentration to the state of anesthesia.
 38. The device of claim 37, wherein the device comprises a flexible portion having the light detector affixed thereto.
 39. The device of claim 38, wherein the flexible portion comprises a disposable material for attaching the flexible portion to the patient.
 40. The device of claim 38, wherein the flexible portion is adapted for adapting to contours of a patient's head for maintaining the light detector in an orientation orthogonal to a surface of the patient's head.
 41. The device of claim 38, wherein the flexible portion comprises a reusable circuit board for housing the light detector.
 42. The device of claim 37, further comprising a light source for directing wavelengths of light in a near-infrared range.
 43. The device of claim 42, wherein the light source has a peak wavelength of at least one of 730 nm, 805 nm, or 850 nm.
 44. The device of claim 42, wherein the device comprises a flexible portion having the light source affixed thereto.
 45. The device of claim 37, further comprising a data acquisition board for switching between a plurality of light sources.
 46. The device of claim 37, further comprising a data acquisition board for switching between a plurality of light detectors.
 47. The device of claim 37, wherein the deoxyhemoglobin concentration is relative to a baseline functional near-infrared signal recorded prior to an administration of an anesthetic.
 48. The device of claim 47, wherein the processor executes computer-executable instructions for determining the deoxyhemoglobin concentration relative to the baseline, and correlating the percentage of the deoxyhemoglobin concentration to the state of anesthesia.
 49. The device of claim 37, wherein the light detector captures a non-cortical signal, the non-cortical signal indicative of an artifact, wherein the processor implements a switch algorithm to select between a principal component analysis (PCA) and an independent component analysis (ICA) noise removal algorithm to remove an effect of the artifact from the functional near-infrared signal by subtracting a portion of the non-cortical signal from the functional near-infrared signal.
 50. A method of removing an effect of an artifact on a functional near-infrared signal, the method comprising: capturing a non-cortical signal, wherein the non-cortical signal is indicative of the artifact; implementing a switch algorithm to select between a principal component analysis (PCA) and an independent component analysis (ICA) noise removal algorithm; removing the effect of the artifact from the functional near-infrared signal by subtracting a portion of the non-cortical signal from the functional near-infrared signal using the selected noise removal algorithm.
 51. The method of claim 50, wherein the non-cortical signal is captured using a reference optode.
 52. The method of claim 50, wherein artifacts resulting in non-cortical signals comprise at least one of a lighting level, change in lighting, table tilting, movement of a patient, patient intubation, or patient extubation.
 53. The method of claim 50, wherein the functional near-infrared signal comprises light having at least three wavelengths in a near-infrared range.
 54. The method of claim 53, wherein at least one wavelength is emitted to capture a reference signal intensity of the non-cortical signal during a period of minimal activation.
 55. The method of claim 54, further comprising receiving a functional near-infrared signal in response to at least two of the wavelengths to determine a deoxyhemoglobin concentration and an oxyhemoglobin concentration
 56. The method of claim 55, further comprising measuring an optical density change of the functional near-infrared signal for the at least two of the wavelengths that correlate to the reference signal intensity. 